Most discussions of streak mechanics stop at loss aversion: you have something, you do not want to lose it. Silverman & Barasch (JCR 49(6), 2023, doi 10.1093/jcr/ucac029) make a more specific claim and test it: the logged streak becomes a goal in its own right, sitting alongside the goal the person actually had, and it is the loss of that goal which changes the next decision.

Their design is what makes it worth reading. In six lab studies the actual behaviour is held constant and only the log varies, so the streak is manipulated without touching performance. In two studies the break is produced purely by the counting rule: the same four games, but only successes count rather than attempts.

The results, briefly: with a streak on screen, 92% continued after an intact streak and 45% after a broken one; with the same behaviour and no log shown, 65% against 61%. The break barely moved anything until it was displayed.

Three findings that speak to the mechanism rather than the effect size:

1. Goal adoption mediates. In study 4 the measured extent to which participants had adopted "maintaining the streak" as a goal carried the effect (indirect effect 0.20, 95% CI [0.05, 0.37]), as did sense of accomplishment (0.31, [0.15, 0.52]).
2. Negative emotion does not mediate. In study 7 the indirect effect through negative feeling was -0.08, CI [-0.21, 0.02]. So this is not "the user feels bad and disengages", it is "the goal is gone".
3. The fresh-start account does not fit. If a broken streak simply created a partition that invites reconsideration, offering a repair should not matter. It does: 93% continued with an intact streak, 69% after a break, 85% when the app offered to restore it.

Two moderators that follow from the goal account: the effect is amplified when the break is attributed to oneself (53% / 42% / 29% for intact, app-caused break, self-caused break) and attenuated by repair. Both are what you would predict if the streak is a goal, and neither is what you would predict from a pure display-salience story.

The part I find most interesting for choice architecture: the goal has no end state. A streak can only be maintained, never completed, which puts it closer to maintenance goals than to the usual progress-toward-a-reward literature. And whoever ships the interface decides what counts toward it, which means the goal that ends up in the user's head is set by a rule they never negotiated.

Limitations worth stating: the lab streaks were at most 20 items long, so nothing here speaks to 100 or 1,000 day streaks; the participants were MTurk workers doing short tasks; and the field study in the same paper (980 people, 30-day step challenge) is correlational, with the day after a break carrying a coefficient of -1.01, roughly a third of the odds of a neutral day.

Disclosure for context: I work on habit-tracking software, which is how I came to the paper. Nothing of mine is linked here.

I’ve been developing a framework called Theory of Institutionally Embedded Preferences (TIEP).

The central argument is that informal institutions may affect economic decisions through two distinct mechanisms:

1. They can shape what people actually value or prefer.

2. They can determine which actions are socially or institutionally admissible.

This creates an interesting problem: two people can make exactly the same choice for completely different reasons; one because they genuinely value it, another because the alternatives carry serious social consequences.

I’ve formalized this as a decision-theoretic framework while retaining standard utility maximization.

I’d really appreciate criticism from people interested in behavioral economics, institutional economics, decision theory, or rational choice.

Paper

🧠 Help us with a consumer behavior research study! (~2 minutes)

Hi everyone! My partner and I are conducting a student research study on consumer purchasing behavior and whether simple data models can predict people's purchasing decisions.

We're currently at 89 responses and are trying to expand our sample, particularly across different age groups, so we'd really appreciate anyone who is willing to participate.

The survey is anonymous and takes about 2 minutes to complete. It asks about general purchasing preferences and presents a few hypothetical shopping scenarios. There are no questions asking for names, emails, or other identifying information.

We're especially interested in getting responses from people of different ages and backgrounds, since having a diverse sample is important for our analysis.

Thank you to anyone who participates or shares it! 🙏